Hardware normalization for a managed network

ABSTRACT

An embodiment involves persistent storage and one or more processors. The persistent storage may contain a plurality of hardware models specifying types of computing devices, wherein the hardware models include attributes representing manufacturer names, product names, and model numbers of the computing devices. The processors may be configured to: obtain, from the persistent storage, a hardware model; calculate a hash value over attributes of the hardware model; compare the hash value to hash values in a curated list, the curated list including normalized hardware models that map the hash values to normalized manufacturer names, normalized product names, or normalized model numbers; determine that the hash value matches a particular hash value for a normalized hardware model; and update, in the persistent storage, the hardware model to include at least one of a normalized manufacturer name, a normalized product name, or a normalized model number associated with the normalized hardware model.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to India Patent Application No.202011000171, filed Jan. 2, 2020, which is hereby incorporated byreference in its entirety.

BACKGROUND

Enterprises may use one or more discovery tools to automaticallyidentify and track computing hardware (e.g., routers, servers, loadbalancers) disposed upon their managed networks. These tools mayidentify the units of hardware by their respective manufacturer names,product names, model numbers, and/or other attributes, and storerepresentations of the identified units as configuration items in adatabase. But each tool may use different criteria for forming suchattributes—for example, one tool may refer to the manufacturer of arouter as “ABC Corporation”, another may refer to the manufacturer as“ABC Corp.” and yet another may refer to the manufacturer as just “ABC”.Further, users may manually enter configuration items into the databaseor upload them in bulk (e.g., from a spreadsheet). As a consequence, thesame type of hardware might be identified in different ways, whichreduces the utility of discovered configuration items and the database.

SUMMARY

The embodiments herein provide a normalization process for hardwarediscovered on a managed network. Particularly, discovery and/or manualprocesses may populate a database (e.g., a configuration managementdatabase, or CMDB) with configuration items related to the hardware. Theconfiguration items may contain or refer to information that defines amanufacturer name, product name, and/or a model number of the discoveredhardware (e.g., a hardware model). Entries for new hardware models maybe added during discovery or manual updates of the database. As notedabove, the hardware can represented by multiple hardware models due tothe use of different discovery tools, errors during manual editing, orthe manufacturers themselves using different attribute values tocharacterize the hardware.

Periodically or from time to time, a normalization application maytraverse some or all of the hardware models in the database and attemptto standardize their attributes to canonical values. These canonicalvalues may be defined in a curated list that accurately characterizesthe hardware. Ideally, this can reduce the number of hardware models pertype of hardware down to one, or at least a manageable number close toone.

For example, manufacturer names for “ABC Corporation”, “ABC Corp.”, and“ABC”, may all be normalized to “ABC Corp.” Similar normalization mayoccur for product names, model numbers, and other attributes. Forinstance, the product names of “PowerRoute” and “PowerRouter” may benormalized to “PowerRoute”, and the model numbers “R220”, “R220v2”, and“R220-2” may be normalized to “R220”.

The normalized values for attributes representing manufacturer names,product names, model numbers, and/or other normalized attributes may bewritten to the appropriate database tables. In this fashion, the sameunits of hardware that are characterized differently in the database canbe re-characterized in a consistent fashion. Configuration itemsreferring to these models may then benefit from this accuracy, thusdramatically improving the utility of the database.

Further, depending on how a manufacturer name, product name, or modelentry is normalized, it may be updated with an indication of itsnormalization status. Supported normalization statuses may include new(normalization has not yet taken place for the entry), normalized (theentry was matched to a canonical entry in the curated list based on itsmanufacturer name, model name, and model number), partially normalized(the entry was matched to a canonical entry in the curated list based onits product name or a combination of its manufacturer name and productname), manufacturer normalized (the entry was matched to a canonicalentry in the curated list based just on its manufacturer name), manuallynormalized (the entry was normalized when a user updated one or more ofits manufacturer name, model name, model number, or device type), andmatch not found (the entry could not be matched to any canonical entryin the curated list).

Moreover, the curated list may include, for each model referencedtherein, indications of the following dates (if known): end of sale, endof life, end of support, end of extended support. This information canbe used by a remote network management platform to provide an overviewof hardware that is approaching or has passed any of these dates.

Accordingly, a first example embodiment may involve a computationalinstance of a remote network management platform, the computationalinstance including persistent storage and one or more processors. Thepersistent storage may contain a plurality of hardware models, thehardware models specifying types of computing devices that are disposedupon a managed network associated with the computational instance,wherein the hardware models respectively include attributes representingmanufacturer names, product names, and model numbers of the computingdevices. The one or more processors may be configured to: (i) obtain,from the persistent storage, a hardware model of the plurality ofhardware models; (ii) calculate a hash value by applying a hash functionto at least some of the attributes of the hardware model; (iii) comparethe hash value to a plurality of hash values in a curated hardware list,wherein the curated hardware list includes normalized hardware modelsthat map the hash values to normalized manufacturer names, normalizedproduct names, or normalized model numbers; (iv) determine that the hashvalue calculated for the hardware model matches a particular hash valuefor a normalized hardware model in the curated hardware list; and (v)update, in the persistent storage, the hardware model to include atleast one of a normalized manufacturer name, a normalized product name,or a normalized model number associated with the normalized hardwaremodel.

A second example embodiment may involve obtaining, from persistentstorage of a computational instance, a hardware model of a plurality ofhardware models, the hardware models specifying types of computingdevices that are disposed upon a managed network associated with thecomputational instance, wherein the hardware models respectively includeattributes representing manufacturer names, product names, and modelnumbers of the computing devices. The second example embodiment mayfurther involve calculating a hash value by applying a hash function toat least some of the attributes of the hardware model. The secondexample embodiment may further involve comparing the hash value to aplurality of hash values in a curated hardware list, wherein the curatedhardware list includes normalized hardware models that map the hashvalues to normalized manufacturer names, normalized product names, ornormalized model numbers. The second example embodiment may furtherinvolve determining that the hash value calculated for the hardwaremodel matches a particular hash value for a normalized hardware model inthe curated hardware list. The second example embodiment may furtherinvolve updating, in the persistent storage, the hardware model toinclude at least one of a normalized manufacturer name, a normalizedproduct name, or a normalized model number associated with thenormalized hardware model.

In a third example embodiment, an article of manufacture may include anon-transitory computer-readable medium, having stored thereon programinstructions that, upon execution by a computing system, cause thecomputing system to perform operations in accordance with the firstand/or second example embodiment.

In a fourth example embodiment, a computing system may include at leastone processor, as well as memory and program instructions. The programinstructions may be stored in the memory, and upon execution by the atleast one processor, cause the computing system to perform operations inaccordance with the first and/or second example embodiment.

In a fifth example embodiment, a system may include various means forcarrying out each of the operations of the first and/or second exampleembodiment.

These, as well as other embodiments, aspects, advantages, andalternatives, will become apparent to those of ordinary skill in the artby reading the following detailed description, with reference whereappropriate to the accompanying drawings. Further, this summary andother descriptions and figures provided herein are intended toillustrate embodiments by way of example only and, as such, thatnumerous variations are possible. For instance, structural elements andprocess steps can be rearranged, combined, distributed, eliminated, orotherwise changed, while remaining within the scope of the embodimentsas claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic drawing of a computing device, inaccordance with example embodiments.

FIG. 2 illustrates a schematic drawing of a server device cluster, inaccordance with example embodiments.

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments.

FIG. 4 depicts a communication environment involving a remote networkmanagement architecture, in accordance with example embodiments.

FIG. 5A depicts another communication environment involving a remotenetwork management architecture, in accordance with example embodiments.

FIG. 5B is a flow chart, in accordance with example embodiments.

FIG. 6 is a schematic diagram representing hardware normalization, inaccordance with example embodiments.

FIG. 7 depicts a curated hardware list, in accordance with exampleembodiments.

FIG. 8 is a flow chart that case be used to determine a normalizationstatus of a hardware model, in accordance with example embodiments.

FIGS. 9A, 9B, 9C, 9D, and 9E depict graphical user interfaces, inaccordance with example embodiments.

FIG. 10 is a flow chart, in accordance with example embodiments.

DETAILED DESCRIPTION

Example methods, devices, and systems are described herein. It should beunderstood that the words “example” and “exemplary” are used herein tomean “serving as an example, instance, or illustration.” Any embodimentor feature described herein as being an “example” or “exemplary” is notnecessarily to be construed as preferred or advantageous over otherembodiments or features unless stated as such. Thus, other embodimentscan be utilized and other changes can be made without departing from thescope of the subject matter presented herein.

Accordingly, the example embodiments described herein are not meant tobe limiting. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations. For example, theseparation of features into “client” and “server” components may occurin a number of ways.

Further, unless context suggests otherwise, the features illustrated ineach of the figures may be used in combination with one another. Thus,the figures should be generally viewed as component aspects of one ormore overall embodiments, with the understanding that not allillustrated features are necessary for each embodiment.

Additionally, any enumeration of elements, blocks, or steps in thisspecification or the claims is for purposes of clarity. Thus, suchenumeration should not be interpreted to require or imply that theseelements, blocks, or steps adhere to a particular arrangement or arecarried out in a particular order.

I. Introduction

A large enterprise is a complex entity with many interrelatedoperations. Some of these are found across the enterprise, such as humanresources (HR), supply chain, information technology (IT), and finance.However, each enterprise also has its own unique operations that provideessential capabilities and/or create competitive advantages.

To support widely-implemented operations, enterprises typically useoff-the-shelf software applications, such as customer relationshipmanagement (CRM) and human capital management (HCM) packages. However,they may also need custom software applications to meet their own uniquerequirements. A large enterprise often has dozens or hundreds of thesecustom software applications. Nonetheless, the advantages provided bythe embodiments herein are not limited to large enterprises and may beapplicable to an enterprise, or any other type of organization, of anysize.

Many such software applications are developed by individual departmentswithin the enterprise. These range from simple spreadsheets tocustom-built software tools and databases. But the proliferation ofsiloed custom software applications has numerous disadvantages. Itnegatively impacts an enterprise's ability to run and grow itsoperations, innovate, and meet regulatory requirements. The enterprisemay find it difficult to integrate, streamline, and enhance itsoperations due to lack of a single system that unifies its subsystemsand data.

To efficiently create custom applications, enterprises would benefitfrom a remotely-hosted application platform that eliminates unnecessarydevelopment complexity. The goal of such a platform would be to reducetime-consuming, repetitive application development tasks so thatsoftware engineers and individuals in other roles can focus ondeveloping unique, high-value features.

In order to achieve this goal, the concept of Application Platform as aService (aPaaS) is introduced, to intelligently automate workflowsthroughout the enterprise. An aPaaS system is hosted remotely from theenterprise, but may access data, applications, and services within theenterprise by way of secure connections. Such an aPaaS system may have anumber of advantageous capabilities and characteristics. Theseadvantages and characteristics may be able to improve the enterprise'soperations and workflows for IT, HR, CRM, customer service, applicationdevelopment, and security.

The aPaaS system may support development and execution ofmodel-view-controller (MVC) applications. MVC applications divide theirfunctionality into three interconnected parts (model, view, andcontroller) in order to isolate representations of information from themanner in which the information is presented to the user, therebyallowing for efficient code reuse and parallel development. Theseapplications may be web-based, and offer create, read, update, delete(CRUD) capabilities. This allows new applications to be built on acommon application infrastructure.

The aPaaS system may support standardized application components, suchas a standardized set of widgets for graphical user interface (GUI)development. In this way, applications built using the aPaaS system havea common look and feel. Other software components and modules may bestandardized as well. In some cases, this look and feel can be brandedor skinned with an enterprise's custom logos and/or color schemes.

The aPaaS system may support the ability to configure the behavior ofapplications using metadata. This allows application behaviors to berapidly adapted to meet specific needs. Such an approach reducesdevelopment time and increases flexibility. Further, the aPaaS systemmay support GUI tools that facilitate metadata creation and management,thus reducing errors in the metadata.

The aPaaS system may support clearly-defined interfaces betweenapplications, so that software developers can avoid unwantedinter-application dependencies. Thus, the aPaaS system may implement aservice layer in which persistent state information and other data arestored.

The aPaaS system may support a rich set of integration features so thatthe applications thereon can interact with legacy applications andthird-party applications. For instance, the aPaaS system may support acustom employee-onboarding system that integrates with legacy HR, IT,and accounting systems.

The aPaaS system may support enterprise-grade security. Furthermore,since the aPaaS system may be remotely hosted, it should also utilizesecurity procedures when it interacts with systems in the enterprise orthird-party networks and services hosted outside of the enterprise. Forexample, the aPaaS system may be configured to share data amongst theenterprise and other parties to detect and identify common securitythreats.

Other features, functionality, and advantages of an aPaaS system mayexist. This description is for purpose of example and is not intended tobe limiting.

As an example of the aPaaS development process, a software developer maybe tasked to create a new application using the aPaaS system. First, thedeveloper may define the data model, which specifies the types of datathat the application uses and the relationships therebetween. Then, viaa GUI of the aPaaS system, the developer enters (e.g., uploads) the datamodel. The aPaaS system automatically creates all of the correspondingdatabase tables, fields, and relationships, which can then be accessedvia an object-oriented services layer.

In addition, the aPaaS system can also build a fully-functional MVCapplication with client-side interfaces and server-side CRUD logic. Thisgenerated application may serve as the basis of further development forthe user. Advantageously, the developer does not have to spend a largeamount of time on basic application functionality. Further, since theapplication may be web-based, it can be accessed from anyInternet-enabled client device. Alternatively or additionally, a localcopy of the application may be able to be accessed, for instance, whenInternet service is not available.

The aPaaS system may also support a rich set of pre-definedfunctionality that can be added to applications. These features includesupport for searching, email, templating, workflow design, reporting,analytics, social media, scripting, mobile-friendly output, andcustomized GUIs.

Such an aPaaS system may represent a GUI in various ways. For example, aserver device of the aPaaS system may generate a representation of a GUIusing a combination of HTML and JAVASCRIPT®. The JAVASCRIPT® may includeclient-side executable code, server-side executable code, or both. Theserver device may transmit or otherwise provide this representation to aclient device for the client device to display on a screen according toits locally-defined look and feel. Alternatively, a representation of aGUI may take other forms, such as an intermediate form (e.g., JAVA®byte-code) that a client device can use to directly generate graphicaloutput therefrom. Other possibilities exist.

Further, user interaction with GUI elements, such as buttons, menus,tabs, sliders, checkboxes, toggles, etc. may be referred to as“selection”, “activation”, or “actuation” thereof. These terms may beused regardless of whether the GUI elements are interacted with by wayof keyboard, pointing device, touchscreen, or another mechanism.

An aPaaS architecture is particularly powerful when integrated with anenterprise's network and used to manage such a network. The followingembodiments describe architectural and functional aspects of exampleaPaaS systems, as well as the features and advantages thereof.

II. Example Computing Devices and Cloud-Based Computing Environments

FIG. 1 is a simplified block diagram exemplifying a computing device100, illustrating some of the components that could be included in acomputing device arranged to operate in accordance with the embodimentsherein. Computing device 100 could be a client device (e.g., a deviceactively operated by a user), a server device (e.g., a device thatprovides computational services to client devices), or some other typeof computational platform. Some server devices may operate as clientdevices from time to time in order to perform particular operations, andsome client devices may incorporate server features.

In this example, computing device 100 includes processor 102, memory104, network interface 106, and input/output unit 108, all of which maybe coupled by system bus 110 or a similar mechanism. In someembodiments, computing device 100 may include other components and/orperipheral devices (e.g., detachable storage, printers, and so on).

Processor 102 may be one or more of any type of computer processingelement, such as a central processing unit (CPU), a co-processor (e.g.,a mathematics, graphics, or encryption co-processor), a digital signalprocessor (DSP), a network processor, and/or a form of integratedcircuit or controller that performs processor operations. In some cases,processor 102 may be one or more single-core processors. In other cases,processor 102 may be one or more multi-core processors with multipleindependent processing units. Processor 102 may also include registermemory for temporarily storing instructions being executed and relateddata, as well as cache memory for temporarily storing recently-usedinstructions and data.

Memory 104 may be any form of computer-usable memory, including but notlimited to random access memory (RAM), read-only memory (ROM), andnon-volatile memory (e.g., flash memory, hard disk drives, solid statedrives, compact discs (CDs), digital video discs (DVDs), and/or tapestorage). Thus, memory 104 represents both main memory units, as well aslong-term storage. Other types of memory may include biological memory.

Memory 104 may store program instructions and/or data on which programinstructions may operate. By way of example, memory 104 may store theseprogram instructions on a non-transitory, computer-readable medium, suchthat the instructions are executable by processor 102 to carry out anyof the methods, processes, or operations disclosed in this specificationor the accompanying drawings.

As shown in FIG. 1, memory 104 may include firmware 104A, kernel 104B,and/or applications 104C. Firmware 104A may be program code used to bootor otherwise initiate some or all of computing device 100. Kernel 104Bmay be an operating system, including modules for memory management,scheduling and management of processes, input/output, and communication.Kernel 104B may also include device drivers that allow the operatingsystem to communicate with the hardware modules (e.g., memory units,networking interfaces, ports, and buses) of computing device 100.Applications 104C may be one or more user-space software programs, suchas web browsers or email clients, as well as any software libraries usedby these programs. Memory 104 may also store data used by these andother programs and applications.

Network interface 106 may take the form of one or more wirelineinterfaces, such as Ethernet (e.g., Fast Ethernet, Gigabit Ethernet, andso on). Network interface 106 may also support communication over one ormore non-Ethernet media, such as coaxial cables or power lines, or overwide-area media, such as Synchronous Optical Networking (SONET) ordigital subscriber line (DSL) technologies. Network interface 106 mayadditionally take the form of one or more wireless interfaces, such asIEEE 802.11 (Wifi), BLUETOOTH®, global positioning system (GPS), or awide-area wireless interface. However, other forms of physical layerinterfaces and other types of standard or proprietary communicationprotocols may be used over network interface 106. Furthermore, networkinterface 106 may comprise multiple physical interfaces. For instance,some embodiments of computing device 100 may include Ethernet,BLUETOOTH®, and Wifi interfaces.

Input/output unit 108 may facilitate user and peripheral deviceinteraction with computing device 100. Input/output unit 108 may includeone or more types of input devices, such as a keyboard, a mouse, a touchscreen, and so on. Similarly, input/output unit 108 may include one ormore types of output devices, such as a screen, monitor, printer, and/orone or more light emitting diodes (LEDs). Additionally or alternatively,computing device 100 may communicate with other devices using auniversal serial bus (USB) or high-definition multimedia interface(HDMI) port interface, for example.

In some embodiments, one or more computing devices like computing device100 may be deployed to support an aPaaS architecture. The exact physicallocation, connectivity, and configuration of these computing devices maybe unknown and/or unimportant to client devices. Accordingly, thecomputing devices may be referred to as “cloud-based” devices that maybe housed at various remote data center locations.

FIG. 2 depicts a cloud-based server cluster 200 in accordance withexample embodiments. In FIG. 2, operations of a computing device (e.g.,computing device 100) may be distributed between server devices 202,data storage 204, and routers 206, all of which may be connected bylocal cluster network 208. The number of server devices 202, datastorages 204, and routers 206 in server cluster 200 may depend on thecomputing task(s) and/or applications assigned to server cluster 200.

For example, server devices 202 can be configured to perform variouscomputing tasks of computing device 100. Thus, computing tasks can bedistributed among one or more of server devices 202. To the extent thatthese computing tasks can be performed in parallel, such a distributionof tasks may reduce the total time to complete these tasks and return aresult. For purposes of simplicity, both server cluster 200 andindividual server devices 202 may be referred to as a “server device.”This nomenclature should be understood to imply that one or moredistinct server devices, data storage devices, and cluster routers maybe involved in server device operations.

Data storage 204 may be data storage arrays that include drive arraycontrollers configured to manage read and write access to groups of harddisk drives and/or solid state drives. The drive array controllers,alone or in conjunction with server devices 202, may also be configuredto manage backup or redundant copies of the data stored in data storage204 to protect against drive failures or other types of failures thatprevent one or more of server devices 202 from accessing units of datastorage 204. Other types of memory aside from drives may be used.

Routers 206 may include networking equipment configured to provideinternal and external communications for server cluster 200. Forexample, routers 206 may include one or more packet-switching and/orrouting devices (including switches and/or gateways) configured toprovide (i) network communications between server devices 202 and datastorage 204 via local cluster network 208, and/or (ii) networkcommunications between server cluster 200 and other devices viacommunication link 210 to network 212.

Additionally, the configuration of routers 206 can be based at least inpart on the data communication requirements of server devices 202 anddata storage 204, the latency and throughput of the local clusternetwork 208, the latency, throughput, and cost of communication link210, and/or other factors that may contribute to the cost, speed,fault-tolerance, resiliency, efficiency, and/or other design goals ofthe system architecture.

As a possible example, data storage 204 may include any form ofdatabase, such as a structured query language (SQL) database. Varioustypes of data structures may store the information in such a database,including but not limited to tables, arrays, lists, trees, and tuples.Furthermore, any databases in data storage 204 may be monolithic ordistributed across multiple physical devices.

Server devices 202 may be configured to transmit data to and receivedata from data storage 204. This transmission and retrieval may take theform of SQL queries or other types of database queries, and the outputof such queries, respectively. Additional text, images, video, and/oraudio may be included as well. Furthermore, server devices 202 mayorganize the received data into web page or web applicationrepresentations. Such a representation may take the form of a markuplanguage, such as the hypertext markup language (HTML), the extensiblemarkup language (XML), or some other standardized or proprietary format.Moreover, server devices 202 may have the capability of executingvarious types of computerized scripting languages, such as but notlimited to Perl, Python, PHP Hypertext Preprocessor (PHP), Active ServerPages (ASP), JAVASCRIPT®, and so on. Computer program code written inthese languages may facilitate the providing of web pages to clientdevices, as well as client device interaction with the web pages.Alternatively or additionally, JAVA® may be used to facilitategeneration of web pages and/or to provide web application functionality.

III. Example Remote Network Management Architecture

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments. This architecture includes three maincomponents—managed network 300, remote network management platform 320,and public cloud networks 340—all connected by way of Internet 350.

A. Managed Networks

Managed network 300 may be, for example, an enterprise network used byan entity for computing and communications tasks, as well as storage ofdata. Thus, managed network 300 may include client devices 302, serverdevices 304, routers 306, virtual machines 308, firewall 310, and/orproxy servers 312. Client devices 302 may be embodied by computingdevice 100, server devices 304 may be embodied by computing device 100or server cluster 200, and routers 306 may be any type of router,switch, or gateway.

Virtual machines 308 may be embodied by one or more of computing device100 or server cluster 200. In general, a virtual machine is an emulationof a computing system, and mimics the functionality (e.g., processor,memory, and communication resources) of a physical computer. Onephysical computing system, such as server cluster 200, may support up tothousands of individual virtual machines. In some embodiments, virtualmachines 308 may be managed by a centralized server device orapplication that facilitates allocation of physical computing resourcesto individual virtual machines, as well as performance and errorreporting. Enterprises often employ virtual machines in order toallocate computing resources in an efficient, as needed fashion.Providers of virtualized computing systems include VMWARE® andMICROSOFT®.

Firewall 310 may be one or more specialized routers or server devicesthat protect managed network 300 from unauthorized attempts to accessthe devices, applications, and services therein, while allowingauthorized communication that is initiated from managed network 300.Firewall 310 may also provide intrusion detection, web filtering, virusscanning, application-layer gateways, and other applications orservices. In some embodiments not shown in FIG. 3, managed network 300may include one or more virtual private network (VPN) gateways withwhich it communicates with remote network management platform 320 (seebelow).

Managed network 300 may also include one or more proxy servers 312. Anembodiment of proxy servers 312 may be a server application thatfacilitates communication and movement of data between managed network300, remote network management platform 320, and public cloud networks340. In particular, proxy servers 312 may be able to establish andmaintain secure communication sessions with one or more computationalinstances of remote network management platform 320. By way of such asession, remote network management platform 320 may be able to discoverand manage aspects of the architecture and configuration of managednetwork 300 and its components. Possibly with the assistance of proxyservers 312, remote network management platform 320 may also be able todiscover and manage aspects of public cloud networks 340 that are usedby managed network 300.

Firewalls, such as firewall 310, typically deny all communicationsessions that are incoming by way of Internet 350, unless such a sessionwas ultimately initiated from behind the firewall (i.e., from a deviceon managed network 300) or the firewall has been explicitly configuredto support the session. By placing proxy servers 312 behind firewall 310(e.g., within managed network 300 and protected by firewall 310), proxyservers 312 may be able to initiate these communication sessions throughfirewall 310. Thus, firewall 310 might not have to be specificallyconfigured to support incoming sessions from remote network managementplatform 320, thereby avoiding potential security risks to managednetwork 300.

In some cases, managed network 300 may consist of a few devices and asmall number of networks. In other deployments, managed network 300 mayspan multiple physical locations and include hundreds of networks andhundreds of thousands of devices. Thus, the architecture depicted inFIG. 3 is capable of scaling up or down by orders of magnitude.

Furthermore, depending on the size, architecture, and connectivity ofmanaged network 300, a varying number of proxy servers 312 may bedeployed therein. For example, each one of proxy servers 312 may beresponsible for communicating with remote network management platform320 regarding a portion of managed network 300. Alternatively oradditionally, sets of two or more proxy servers may be assigned to sucha portion of managed network 300 for purposes of load balancing,redundancy, and/or high availability.

B. Remote Network Management Platforms

Remote network management platform 320 is a hosted environment thatprovides aPaaS services to users, particularly to the operator ofmanaged network 300. These services may take the form of web-basedportals, for example, using the aforementioned web-based technologies.Thus, a user can securely access remote network management platform 320from, for example, client devices 302, or potentially from a clientdevice outside of managed network 300. By way of the web-based portals,users may design, test, and deploy applications, generate reports, viewanalytics, and perform other tasks.

As shown in FIG. 3, remote network management platform 320 includes fourcomputational instances 322, 324, 326, and 328. Each of thesecomputational instances may represent one or more server nodes operatingdedicated copies of the aPaaS software and/or one or more databasenodes. The arrangement of server and database nodes on physical serverdevices and/or virtual machines can be flexible and may vary based onenterprise needs. In combination, these nodes may provide a set of webportals, services, and applications (e.g., a wholly-functioning aPaaSsystem) available to a particular enterprise. In some cases, a singleenterprise may use multiple computational instances.

For example, managed network 300 may be an enterprise customer of remotenetwork management platform 320, and may use computational instances322, 324, and 326. The reason for providing multiple computationalinstances to one customer is that the customer may wish to independentlydevelop, test, and deploy its applications and services. Thus,computational instance 322 may be dedicated to application developmentrelated to managed network 300, computational instance 324 may bededicated to testing these applications, and computational instance 326may be dedicated to the live operation of tested applications andservices. A computational instance may also be referred to as a hostedinstance, a remote instance, a customer instance, or by some otherdesignation. Any application deployed onto a computational instance maybe a scoped application, in that its access to databases within thecomputational instance can be restricted to certain elements therein(e.g., one or more particular database tables or particular rows withinone or more database tables).

For purposes of clarity, the disclosure herein refers to the arrangementof application nodes, database nodes, aPaaS software executing thereon,and underlying hardware as a “computational instance.” Note that usersmay colloquially refer to the graphical user interfaces provided therebyas “instances.” But unless it is defined otherwise herein, a“computational instance” is a computing system disposed within remotenetwork management platform 320.

The multi-instance architecture of remote network management platform320 is in contrast to conventional multi-tenant architectures, overwhich multi-instance architectures exhibit several advantages. Inmulti-tenant architectures, data from different customers (e.g.,enterprises) are comingled in a single database. While these customers'data are separate from one another, the separation is enforced by thesoftware that operates the single database. As a consequence, a securitybreach in this system may impact all customers' data, creatingadditional risk, especially for entities subject to governmental,healthcare, and/or financial regulation. Furthermore, any databaseoperations that impact one customer will likely impact all customerssharing that database. Thus, if there is an outage due to hardware orsoftware errors, this outage affects all such customers. Likewise, ifthe database is to be upgraded to meet the needs of one customer, itwill be unavailable to all customers during the upgrade process. Often,such maintenance windows will be long, due to the size of the shareddatabase.

In contrast, the multi-instance architecture provides each customer withits own database in a dedicated computing instance. This preventscomingling of customer data, and allows each instance to beindependently managed. For example, when one customer's instanceexperiences an outage due to errors or an upgrade, other computationalinstances are not impacted. Maintenance down time is limited because thedatabase only contains one customer's data. Further, the simpler designof the multi-instance architecture allows redundant copies of eachcustomer database and instance to be deployed in a geographicallydiverse fashion. This facilitates high availability, where the liveversion of the customer's instance can be moved when faults are detectedor maintenance is being performed.

In some embodiments, remote network management platform 320 may includeone or more central instances, controlled by the entity that operatesthis platform. Like a computational instance, a central instance mayinclude some number of application and database nodes disposed upon somenumber of physical server devices or virtual machines. Such a centralinstance may serve as a repository for specific configurations ofcomputational instances as well as data that can be shared amongst atleast some of the computational instances. For instance, definitions ofcommon security threats that could occur on the computational instances,software packages that are commonly discovered on the computationalinstances, and/or an application store for applications that can bedeployed to the computational instances may reside in a centralinstance. Computational instances may communicate with central instancesby way of well-defined interfaces in order to obtain this data.

In order to support multiple computational instances in an efficientfashion, remote network management platform 320 may implement aplurality of these instances on a single hardware platform. For example,when the aPaaS system is implemented on a server cluster such as servercluster 200, it may operate virtual machines that dedicate varyingamounts of computational, storage, and communication resources toinstances. But full virtualization of server cluster 200 might not benecessary, and other mechanisms may be used to separate instances. Insome examples, each instance may have a dedicated account and one ormore dedicated databases on server cluster 200. Alternatively, acomputational instance such as computational instance 322 may spanmultiple physical devices.

In some cases, a single server cluster of remote network managementplatform 320 may support multiple independent enterprises. Furthermore,as described below, remote network management platform 320 may includemultiple server clusters deployed in geographically diverse data centersin order to facilitate load balancing, redundancy, and/or highavailability.

C. Public Cloud Networks

Public cloud networks 340 may be remote server devices (e.g., aplurality of server clusters such as server cluster 200) that can beused for outsourced computation, data storage, communication, andservice hosting operations. These servers may be virtualized (i.e., theservers may be virtual machines). Examples of public cloud networks 340may include AMAZON WEB SERVICES® and MICROSOFT® AZURE®. Like remotenetwork management platform 320, multiple server clusters supportingpublic cloud networks 340 may be deployed at geographically diverselocations for purposes of load balancing, redundancy, and/or highavailability.

Managed network 300 may use one or more of public cloud networks 340 todeploy applications and services to its clients and customers. Forinstance, if managed network 300 provides online music streamingservices, public cloud networks 340 may store the music files andprovide web interface and streaming capabilities. In this way, theenterprise of managed network 300 does not have to build and maintainits own servers for these operations.

Remote network management platform 320 may include modules thatintegrate with public cloud networks 340 to expose virtual machines andmanaged services therein to managed network 300. The modules may allowusers to request virtual resources, discover allocated resources, andprovide flexible reporting for public cloud networks 340. In order toestablish this functionality, a user from managed network 300 mightfirst establish an account with public cloud networks 340, and request aset of associated resources. Then, the user may enter the accountinformation into the appropriate modules of remote network managementplatform 320. These modules may then automatically discover themanageable resources in the account, and also provide reports related tousage, performance, and billing.

D. Communication Support and Other Operations

Internet 350 may represent a portion of the global Internet. However,Internet 350 may alternatively represent a different type of network,such as a private wide-area or local-area packet-switched network.

FIG. 4 further illustrates the communication environment between managednetwork 300 and computational instance 322, and introduces additionalfeatures and alternative embodiments. In FIG. 4, computational instance322 is replicated across data centers 400A and 400B. These data centersmay be geographically distant from one another, perhaps in differentcities or different countries. Each data center includes supportequipment that facilitates communication with managed network 300, aswell as remote users.

In data center 400A, network traffic to and from external devices flowseither through VPN gateway 402A or firewall 404A. VPN gateway 402A maybe peered with VPN gateway 412 of managed network 300 by way of asecurity protocol such as Internet Protocol Security (IPSEC) orTransport Layer Security (TLS). Firewall 404A may be configured to allowaccess from authorized users, such as user 414 and remote user 416, andto deny access to unauthorized users. By way of firewall 404A, theseusers may access computational instance 322, and possibly othercomputational instances. Load balancer 406A may be used to distributetraffic amongst one or more physical or virtual server devices that hostcomputational instance 322. Load balancer 406A may simplify user accessby hiding the internal configuration of data center 400A, (e.g.,computational instance 322) from client devices. For instance, ifcomputational instance 322 includes multiple physical or virtualcomputing devices that share access to multiple databases, load balancer406A may distribute network traffic and processing tasks across thesecomputing devices and databases so that no one computing device ordatabase is significantly busier than the others. In some embodiments,computational instance 322 may include VPN gateway 402A, firewall 404A,and load balancer 406A.

Data center 400B may include its own versions of the components in datacenter 400A. Thus, VPN gateway 402B, firewall 404B, and load balancer406B may perform the same or similar operations as VPN gateway 402A,firewall 404A, and load balancer 406A, respectively. Further, by way ofreal-time or near-real-time database replication and/or otheroperations, computational instance 322 may exist simultaneously in datacenters 400A and 400B.

Data centers 400A and 400B as shown in FIG. 4 may facilitate redundancyand high availability. In the configuration of FIG. 4, data center 400Ais active and data center 400B is passive. Thus, data center 400A isserving all traffic to and from managed network 300, while the versionof computational instance 322 in data center 400B is being updated innear-real-time. Other configurations, such as one in which both datacenters are active, may be supported.

Should data center 400A fail in some fashion or otherwise becomeunavailable to users, data center 400B can take over as the active datacenter. For example, domain name system (DNS) servers that associate adomain name of computational instance 322 with one or more InternetProtocol (IP) addresses of data center 400A may re-associate the domainname with one or more IP addresses of data center 400B. After thisre-association completes (which may take less than one second or severalseconds), users may access computational instance 322 by way of datacenter 400B.

FIG. 4 also illustrates a possible configuration of managed network 300.As noted above, proxy servers 312 and user 414 may access computationalinstance 322 through firewall 310. Proxy servers 312 may also accessconfiguration items 410. In FIG. 4, configuration items 410 may refer toany or all of client devices 302, server devices 304, routers 306, andvirtual machines 308, any applications or services executing thereon, aswell as relationships between devices, applications, and services. Thus,the term “configuration items” may be shorthand for any physical orvirtual device, or any application or service remotely discoverable ormanaged by computational instance 322, or relationships betweendiscovered devices, applications, and services. Configuration items maybe represented in a configuration management database (CMDB) ofcomputational instance 322.

As noted above, VPN gateway 412 may provide a dedicated VPN to VPNgateway 402A. Such a VPN may be helpful when there is a significantamount of traffic between managed network 300 and computational instance322, or security policies otherwise suggest or require use of a VPNbetween these sites. In some embodiments, any device in managed network300 and/or computational instance 322 that directly communicates via theVPN is assigned a public IP address. Other devices in managed network300 and/or computational instance 322 may be assigned private IPaddresses (e.g., IP addresses selected from the 10.0.0.0-10.255.255.255or 192.168.0.0-192.168.255.255 ranges, represented in shorthand assubnets 10.0.0.0/8 and 192.168.0.0/16, respectively).

IV. Example Device, Application, and Service Discovery

In order for remote network management platform 320 to administer thedevices, applications, and services of managed network 300, remotenetwork management platform 320 may first determine what devices arepresent in managed network 300, the configurations and operationalstatuses of these devices, and the applications and services provided bythe devices, as well as the relationships between discovered devices,applications, and services. As noted above, each device, application,service, and relationship may be referred to as a configuration item.The process of defining configuration items within managed network 300is referred to as discovery, and may be facilitated at least in part byproxy servers 312.

For purposes of the embodiments herein, an “application” may refer toone or more processes, threads, programs, client modules, servermodules, or any other software that executes on a device or group ofdevices. A “service” may refer to a high-level capability provided bymultiple applications executing on one or more devices working inconjunction with one another. For example, a high-level web service mayinvolve multiple web application server threads executing on one deviceand accessing information from a database application that executes onanother device.

FIG. 5A provides a logical depiction of how configuration items can bediscovered, as well as how information related to discoveredconfiguration items can be stored. For sake of simplicity, remotenetwork management platform 320, public cloud networks 340, and Internet350 are not shown.

In FIG. 5A, CMDB 500 and task list 502 are stored within computationalinstance 322. Computational instance 322 may transmit discovery commandsto proxy servers 312. In response, proxy servers 312 may transmit probesto various devices, applications, and services in managed network 300.These devices, applications, and services may transmit responses toproxy servers 312, and proxy servers 312 may then provide informationregarding discovered configuration items to CMDB 500 for storagetherein. Configuration items stored in CMDB 500 represent theenvironment of managed network 300.

Task list 502 represents a list of activities that proxy servers 312 areto perform on behalf of computational instance 322. As discovery takesplace, task list 502 is populated. Proxy servers 312 repeatedly querytask list 502, obtain the next task therein, and perform this task untiltask list 502 is empty or another stopping condition has been reached.

To facilitate discovery, proxy servers 312 may be configured withinformation regarding one or more subnets in managed network 300 thatare reachable by way of proxy servers 312. For instance, proxy servers312 may be given the IP address range 192.168.0/24 as a subnet. Then,computational instance 322 may store this information in CMDB 500 andplace tasks in task list 502 for discovery of devices at each of theseaddresses.

FIG. 5A also depicts devices, applications, and services in managednetwork 300 as configuration items 504, 506, 508, 510, and 512. As notedabove, these configuration items represent a set of physical and/orvirtual devices (e.g., client devices, server devices, routers, orvirtual machines), applications executing thereon (e.g., web servers,email servers, databases, or storage arrays), relationshipstherebetween, as well as services that involve multiple individualconfiguration items.

Placing the tasks in task list 502 may trigger or otherwise cause proxyservers 312 to begin discovery. Alternatively or additionally, discoverymay be manually triggered or automatically triggered based on triggeringevents (e.g., discovery may automatically begin once per day at aparticular time).

In general, discovery may proceed in four logical phases: scanning,classification, identification, and exploration. Each phase of discoveryinvolves various types of probe messages being transmitted by proxyservers 312 to one or more devices in managed network 300. The responsesto these probes may be received and processed by proxy servers 312, andrepresentations thereof may be transmitted to CMDB 500. Thus, each phasecan result in more configuration items being discovered and stored inCMDB 500.

In the scanning phase, proxy servers 312 may probe each IP address inthe specified range of IP addresses for open Transmission ControlProtocol (TCP) and/or User Datagram Protocol (UDP) ports to determinethe general type of device. The presence of such open ports at an IPaddress may indicate that a particular application is operating on thedevice that is assigned the IP address, which in turn may identify theoperating system used by the device. For example, if TCP port 135 isopen, then the device is likely executing a WINDOWS® operating system.Similarly, if TCP port 22 is open, then the device is likely executing aUNIX® operating system, such as LINUX®. If UDP port 161 is open, thenthe device may be able to be further identified through the SimpleNetwork Management Protocol (SNMP). Other possibilities exist. Once thepresence of a device at a particular IP address and its open ports havebeen discovered, these configuration items are saved in CMDB 500.

In the classification phase, proxy servers 312 may further probe eachdiscovered device to determine the version of its operating system. Theprobes used for a particular device are based on information gatheredabout the devices during the scanning phase. For example, if a device isfound with TCP port 22 open, a set of UNIX®-specific probes may be used.Likewise, if a device is found with TCP port 135 open, a set ofWINDOWS®-specific probes may be used. For either case, an appropriateset of tasks may be placed in task list 502 for proxy servers 312 tocarry out. These tasks may result in proxy servers 312 logging on, orotherwise accessing information from the particular device. Forinstance, if TCP port 22 is open, proxy servers 312 may be instructed toinitiate a Secure Shell (SSH) connection to the particular device andobtain information about the operating system thereon from particularlocations in the file system. Based on this information, the operatingsystem may be determined. As an example, a UNIX® device with TCP port 22open may be classified as AIX®, HPUX, LINUX®, MACOS®, or SOLARIS®. Thisclassification information may be stored as one or more configurationitems in CMDB 500.

In the identification phase, proxy servers 312 may determine specificdetails about a classified device. The probes used during this phase maybe based on information gathered about the particular devices during theclassification phase. For example, if a device was classified as LINUX®,a set of LINUX®-specific probes may be used. Likewise, if a device wasclassified as WINDOWS® 2012, as a set of WINDOWS®-2012-specific probesmay be used. As was the case for the classification phase, anappropriate set of tasks may be placed in task list 502 for proxyservers 312 to carry out. These tasks may result in proxy servers 312reading information from the particular device, such as basicinput/output system (BIOS) information, serial numbers, networkinterface information, media access control address(es) assigned tothese network interface(s), IP address(es) used by the particular deviceand so on. This identification information may be stored as one or moreconfiguration items in CMDB 500.

In the exploration phase, proxy servers 312 may determine furtherdetails about the operational state of a classified device. The probesused during this phase may be based on information gathered about theparticular devices during the classification phase and/or theidentification phase. Again, an appropriate set of tasks may be placedin task list 502 for proxy servers 312 to carry out. These tasks mayresult in proxy servers 312 reading additional information from theparticular device, such as processor information, memory information,lists of running processes (applications), and so on. Once more, thediscovered information may be stored as one or more configuration itemsin CMDB 500.

Running discovery on a network device, such as a router, may utilizeSNMP. Instead of or in addition to determining a list of runningprocesses or other application-related information, discovery maydetermine additional subnets known to the router and the operationalstate of the router's network interfaces (e.g., active, inactive, queuelength, number of packets dropped, etc.). The IP addresses of theadditional subnets may be candidates for further discovery procedures.Thus, discovery may progress iteratively or recursively.

Once discovery completes, a snapshot representation of each discovereddevice, application, and service is available in CMDB 500. For example,after discovery, operating system version, hardware configuration, andnetwork configuration details for client devices, server devices, androuters in managed network 300, as well as applications executingthereon, may be stored. This collected information may be presented to auser in various ways to allow the user to view the hardware compositionand operational status of devices, as well as the characteristics ofservices that span multiple devices and applications.

Furthermore, CMDB 500 may include entries regarding dependencies andrelationships between configuration items. More specifically, anapplication that is executing on a particular server device, as well asthe services that rely on this application, may be represented as suchin CMDB 500. For example, suppose that a database application isexecuting on a server device, and that this database application is usedby a new employee onboarding service as well as a payroll service. Thus,if the server device is taken out of operation for maintenance, it isclear that the employee onboarding service and payroll service will beimpacted. Likewise, the dependencies and relationships betweenconfiguration items may be able to represent the services impacted whena particular router fails.

In general, dependencies and relationships between configuration itemsmay be displayed on a web-based interface and represented in ahierarchical fashion. Thus, adding, changing, or removing suchdependencies and relationships may be accomplished by way of thisinterface.

Furthermore, users from managed network 300 may develop workflows thatallow certain coordinated activities to take place across multiplediscovered devices. For instance, an IT workflow might allow the user tochange the common administrator password to all discovered LINUX®devices in a single operation.

In order for discovery to take place in the manner described above,proxy servers 312, CMDB 500, and/or one or more credential stores may beconfigured with credentials for one or more of the devices to bediscovered. Credentials may include any type of information needed inorder to access the devices. These may include userid/password pairs,certificates, and so on. In some embodiments, these credentials may bestored in encrypted fields of CMDB 500. Proxy servers 312 may containthe decryption key for the credentials so that proxy servers 312 can usethese credentials to log on to or otherwise access devices beingdiscovered.

The discovery process is depicted as a flow chart in FIG. 5B. At block520, the task list in the computational instance is populated, forinstance, with a range of IP addresses. At block 522, the scanning phasetakes place. Thus, the proxy servers probe the IP addresses for devicesusing these IP addresses, and attempt to determine the operating systemsthat are executing on these devices. At block 524, the classificationphase takes place. The proxy servers attempt to determine the operatingsystem version of the discovered devices. At block 526, theidentification phase takes place. The proxy servers attempt to determinethe hardware and/or software configuration of the discovered devices. Atblock 528, the exploration phase takes place. The proxy servers attemptto determine the operational state and applications executing on thediscovered devices. At block 530, further editing of the configurationitems representing the discovered devices and applications may takeplace. This editing may be automated and/or manual in nature.

The blocks represented in FIG. 5B are examples. Discovery may be ahighly configurable procedure that can have more or fewer phases, andthe operations of each phase may vary. In some cases, one or more phasesmay be customized, or may otherwise deviate from the exemplarydescriptions above.

In this manner, a remote network management platform may discover andinventory the hardware, software, and services deployed on and providedby the managed network. As noted above, this data may be stored in aCMDB of the associated computational instance as configuration items.For example, individual hardware components (e.g., computing devices,virtual servers, databases, routers, etc.) may be represented ashardware configuration items, while the applications installed and/orexecuting thereon may be represented as software configuration items.

The relationship between a software configuration item installed orexecuting on a hardware configuration item may take various forms, suchas “is hosted on”, “runs on”, or “depends on”. Thus, a databaseapplication installed on a server device may have the relationship “ishosted on” with the server device to indicate that the databaseapplication is hosted on the server device. In some embodiments, theserver device may have a reciprocal relationship of “used by” with thedatabase application to indicate that the server device is used by thedatabase application. These relationships may be automatically foundusing the discovery procedures described above, though it is possible tomanually set relationships as well.

The relationship between a service and one or more softwareconfiguration items may also take various forms. As an example, a webservice may include a web server software configuration item and adatabase application software configuration item, each installed ondifferent hardware configuration items. The web service may have a“depends on” relationship with both of these software configurationitems, while the software configuration items have a “used by”reciprocal relationship with the web service. Services might not be ableto be fully determined by discovery procedures, and instead may rely onservice mapping (e.g., probing configuration files and/or carrying outnetwork traffic analysis to determine service level relationshipsbetween configuration items) and possibly some extent of manualconfiguration.

Regardless of how relationship information is obtained, it can bevaluable for the operation of a managed network. Notably, IT personnelcan quickly determine where certain software applications are deployed,and what configuration items make up a service. This allows for rapidpinpointing of root causes of service outages or degradation. Forexample, if two different services are suffering from slow responsetimes, the CMDB can be queried (perhaps among other activities) todetermine that the root cause is a database application that is used byboth services having high processor utilization. Thus, IT personnel canaddress the database application rather than waste time considering thehealth and performance of other configuration items that make up theservices.

V. CMDB Identification Rules and Reconciliation

A CMDB, such as CMDB 500, provides a repository of configuration items,and when properly provisioned, can take on a key role in higher-layerapplications deployed within or involving a computational instance.These applications may relate to enterprise IT service management,operations management, asset management, configuration management,compliance, and so on.

For example, an IT service management application may use information inthe CMDB to determine applications and services that may be impacted bya component (e.g., a server device) that has malfunctioned, crashed, oris heavily loaded. Likewise, an asset management application may useinformation in the CMDB to determine which hardware and/or softwarecomponents are being used to support particular enterprise applications.As a consequence of the importance of the CMDB, it is desirable for theinformation stored therein to be accurate, consistent, and up to date.

A CMDB may be populated in various ways. As discussed above, a discoveryprocedure may automatically store information related to configurationitems in the CMDB. However, a CMDB can also be populated, as a whole orin part, by manual entry, configuration files, and third-party datasources. Given that multiple data sources may be able to update the CMDBat any time, it is possible that one data source may overwrite entriesof another data source. Also, two data sources may each create slightlydifferent entries for the same configuration item, resulting in a CMDBcontaining duplicate data. When either of these occurrences takes place,they can cause the health and utility of the CMDB to be reduced.

In order to mitigate this situation, these data sources might not writeconfiguration items directly to the CMDB. Instead, they may write to anidentification and reconciliation application programming interface(API). This API may use a set of configurable identification rules thatcan be used to uniquely identify configuration items and determinewhether and how they are written to the CMDB.

In general, an identification rule specifies a set of configuration itemattributes that can be used for this unique identification.Identification rules may also have priorities so that rules with higherpriorities are considered before rules with lower priorities.Additionally, a rule may be independent, in that the rule identifiesconfiguration items independently of other configuration items.Alternatively, the rule may be dependent, in that the rule first uses ametadata rule to identify a dependent configuration item.

Metadata rules describe which other configuration items are containedwithin a particular configuration item, or the host on which aparticular configuration item is deployed. For example, a networkdirectory service configuration item may contain a domain controllerconfiguration item, while a web server application configuration itemmay be hosted on a server device configuration item.

A goal of each identification rule is to use a combination of attributesthat can unambiguously distinguish a configuration item from all otherconfiguration items, and is expected not to change during the lifetimeof the configuration item. Some possible attributes for an exampleserver device may include serial number, location, operating system,operating system version, memory capacity, and so on. If a rulespecifies attributes that do not uniquely identify the configurationitem, then multiple components may be represented as the sameconfiguration item in the CMDB. Also, if a rule specifies attributesthat change for a particular configuration item, duplicate configurationitems may be created.

Thus, when a data source provides information regarding a configurationitem to the identification and reconciliation API, the API may attemptto match the information with one or more rules. If a match is found,the configuration item is written to the CMDB. If a match is not found,the configuration item may be held for further analysis.

Configuration item reconciliation procedures may be used to ensure thatonly authoritative data sources are allowed to overwrite configurationitem data in the CMDB. This reconciliation may also be rules-based. Forinstance, a reconciliation rule may specify that a particular datasource is authoritative for a particular configuration item type and setof attributes. Then, the identification and reconciliation API will onlypermit this authoritative data source to write to the particularconfiguration item, and writes from unauthorized data sources may beprevented. Thus, the authorized data source becomes the single source oftruth regarding the particular configuration item. In some cases, anunauthorized data source may be allowed to write to a configuration itemif it is creating the configuration item or the attributes to which itis writing are empty.

Additionally, multiple data sources may be authoritative for the sameconfiguration item or attributes thereof. To avoid ambiguities, thesedata sources may be assigned precedences that are taken into accountduring the writing of configuration items. For example, a secondaryauthorized data source may be able to write to a configuration item'sattribute until a primary authorized data source writes to thisattribute. Afterward, further writes to the attribute by the secondaryauthorized data source may be prevented.

In some cases, duplicate configuration items may be automaticallydetected by reconciliation procedures or in another fashion. Theseconfiguration items may be flagged for manual de-duplication.

VI. Hardware Normalization

As noted above, managed networks (such as managed network 300) may havedisposed within them numerous hardware devices, such as laptopcomputers, desktop computers, routers, switches, firewalls, loadbalancers, databases, and so on. These hardware devices may bediscovered and represented as configuration items. Alternatively,configuration items may be bulk uploaded or manually entered into a CMDBfor some of the hardware devices.

Models of hardware devices (referred to herein as “hardware models”) maybe represented by the attributes in Table 1 below. More or fewerattributes may be used. For example, additional attributes may include ashort description, cost, salvage value, and comments.

TABLE 1 Attribute Type Description Manufacturer String The company thatbuilt the model. name Product name String The manufacturer-assigned nameof the model Model number String The specific model number assigned tothe item by the manufacturer. Owner String The person responsible forthe model. Status Enumerated In production, retired, or sold.Configuration References The configuration items created from items thismodel.

In some embodiments, the content of Table 1 may be stored in a singletable in the CMDB. In other embodiments, the CMDB may be arranged withone table for hardware models and another for manufacturers, withentries in the hardware model table referring to entries in themanufacturer table. In either of these possibilities, hardwareconfiguration items may refer to the hardware model table fordefinitions of their hardware model and manufacturer. Nonetheless,database tables can be arranged in various ways and alternativeembodiments are possible. For purposes of simplicity, the descriptionherein assumes a CMDB table (referred to herein as a “model table”)containing some or all of the hardware model information of Table 1, andthat hardware configuration items may refer to the this model table.

As noted previously, due to how the CMDB is populated, there may bemultiple entries in such a model table for hardware devices of the sameactual model. For example, laptop manufacturer Tyrell Corporation mayprovide laptops with a product name of RPC and the model number Z20. Butthe CMDB may have been populated such that there are five actual modelsfor these laptops, as shown in Table 2.

TABLE 2 Model in CMDB Manufacturer name Product name Model number 1Tyrell RPC Z20 2 Tyrell Corp. RPC Z 20 3 Tyrell Inc. RPC Z20 4 TyrellInc. Replicant Z20 5 Tyrel Z 20

These differences may be due to inconsistencies in how various discoveryapplications categorize discovered hardware and/or inconsistencies inhow configuration items were manually entered or updated. To that point,some models in Table 2 use different representations of the manufacturername, misspell the manufacturer name, have a different representation ofthe product name (“Replicant” versus “RPC”), leave the product nameblank, or have an incorrect representation of the model number (e.g.,“Z20” instead of “Z20”).

There may be numerous configuration items referring to each of thesemodels. As a consequence, the CMDB may not accurately or convenientlyrepresent the true deployment extent of the hardware model in question.For example, searching for all instances of the actual hardware modelmay be difficult, as multiple search criteria for the five models inTable 2 would have to be entered. This reduces the utility of the CMDBand any application (e.g., IT service management, IT operationsmanagement, IT asset management) that relies upon data in the CMDB.

In order to mitigate problems related to inconsistent or incompletehardware attributes in the CMDB, hardware normalization can be used. Ingeneral, hardware normalization refers to the act of verifying that themodel table in the CMDB consistently and accurately characterizes actualhardware models, and updating the model table as needed to representhardware models consistently. Hardware normalization can be an automatedprocess that executes periodically or from time to time (e.g., one perday or one per week).

FIG. 6 depicts a schematic diagram 600 representing a possible techniquefor hardware normalization. Discovery applications 602 and 604, bulkupload process 606, and manual entry process 608 may providerepresentations of model information 610 into CMDB 500. For instance, ashardware devices are discovered on a managed network, the discoveryprocess may probe the hardware devices to identify manufacturerinformation thereof (e.g., by reading configuration files, SNMP objects,etc.). This information is then used to either classify the hardwaredevices in accordance with an existing hardware model or to create a newhardware model if the information does not match any existing hardwaremodel. CMDB 500 may, in turn, store this information in entries of amodel table. CMDB 500 may also store configuration items for eachdiscovered hardware device, with these configuration items referring tothe appropriate entries in the model table.

As noted previously, some embodiments may store manufacturerinformation, such as manufacturer names, in a separate table. In theseembodiments, entries in the model table may refer to entries in themanufacturer table rather than have a separate attribute formanufacturer name. But for purposes of simplicity, in the discussionbelow the hardware model will be assumed to be fully specified in onetable.

FIG. 6 also includes curated hardware list 612. This list is manuallyupdated and contains canonical entries (model descriptions 614) for eachknown hardware device. Model descriptions 614 include accurate andconsistent values for manufacturer name, product name, model number, andother information. Curated hardware list 612 will be described in moredetail below. For purposes of the embodiments herein, model descriptions614 of curated hardware list 612 are considered to contain the correctrepresentations of information that could appear in the model table ofCMDB 500. Model descriptions 614 may be referred to a “normalizedhardware models”.

Not unlike the arrangement of the CMDB, models descriptions 614 andmanufacturers may be represented in a logically distinct fashion incurated hardware list 612. For example, a list of canonical manufacturernames may be stored separately from model descriptions 614. Again forpurposes of simplicity, in the discussion below curated hardware list612 will be assumed to contain both hardware model and manufacturerinformation.

Normalization application 618 is a software program or programs thatexecutes within computational instance 322 and/or remote networkmanagement platform 320. It may be configured to execute on a regularbasis (e.g., once per day at a pre-determined time), on the completionof discovery, and/or whenever a new entry in the model table is createdor an existing entry is modified.

Normalization application 618 may obtain model descriptions 614 fromcurated hardware list 612 and model entries 616 from the model table ofCMDB 500. Normalization application 618 may further compare modelentries 616 to model descriptions 614 by applying normalization rules.These normalization rules will be discussed in more detail below.

When an entry in model entries 616 matches one of model descriptions614, normalization application 618 may update the model entry to reflectits normalized values. This may involve overwriting information in themodel entry with the respective normalized values. Alternatively, themodel entries may include attributes for normalized values andnormalization application 618 may update the model entry by adding thenormalized values to the entry while leaving at least some of thediscovered values as is. Regardless, normalization application 618 mayprovide normalized model entries 620 to CMDB 500.

A. Example Curated Model Entry

FIG. 7 depicts curated hardware list 612 in more detail. This list maybe maintained in a central instance of remote network managementplatform 320. Each computational instance therein may be configured toobtain a fresh copy of curated hardware list 612 on a periodic basis orfrom time to time (e.g., once per week).

Entry 700 represents the attributes of a single normalized hardwaremodel within curated hardware list 612. Thus, curated hardware list 612may contain many such entries. Entry 700 is shown for purposes ofexample, and therefore more or fewer attributes may be present.

Manufacturer name 702 represents the name of the hardware manufacturer.In some embodiments, this attribute may be referred to as the“manufacturer” or “vendor”.

Product name 704 represents the name of the hardware product. In someembodiments, this attribute may be referred to as the “product” or“model name”.

Model number 706 represents the model number of the hardware. In someembodiments, this attribute may be referred to as the “model”.

Attributes 708, 710, 712, and 714 represent mappings between hash valuesand normalization statuses. The hash values are predetermined results ofa hash function (e.g., SHA-256 or another sufficiently robust hashfunction) calculated over various combinations of attributes in theentry, each representing a normalization status. In some cases, thedifferent hash values may map to the same normalization status. Use ofattributes 708, 710, 712, and 714 during normalization is describedbelow.

Device type 716 represents a device type of the hardware. Values of theattribute may be, for example, “laptop”, “desktop”, “server”, “router”,and so on.

End of sales 718 represents the last date to order the hardware by wayof the manufacturer. After this date, the hardware is no longer for salefrom the manufacturer.

End of life 720 represents the date on which the hardware reaches theend of its useful life (from the manufacturer's point of view).

End of support 722 represents the date on which the hardware is nolonger supported with new features from the manufacturer.

End of extended support 724 represents the date on which the hardware isno longer supported with patches or bug fixes from the manufacturer.Often, extended support requires a specific contract to be in placebetween the manufacturer and the entity receiving the extended support.

In some embodiments, the definitions of end of sales 718, end of life720, end of support 722, and end of extended support 724 may vary and/oroverlap to some extent. Different manufacturers may interpret thesedates differently. Further, some of these dates may be blank or empty inentry 700 because they have not yet been announced by the manufacturer.

Notably, end of sales 718, end of life 720, end of support 722, and endof extended support 724 cannot be discovered and are instead manuallycurated. Nonetheless, they provide valuable information to ITprofessionals managing an enterprise.

B. Example Normalization Algorithm

FIG. 8 depicts flow chart 800, representing a normalization procedure.As noted above, normalization may be carried out by normalizationapplication 618 executing on computational instance 322 of remotenetwork management platform 320.

At block 802, normalization application 618 receives model entries 616from CMDB 500 and calculates a hash function one or more times overvarious combinations of attributes in each of these entries. In oneexample, the hash function may take as input a concatenation of themanufacturer name, product name, and model number of a model entry. Inanother example, the hash function may take as input a concatenation ofthe manufacturer name and model number of a model entry.

Various types of delimiters may be placed between these attributes. Forexample, space delimiters may be used so that the concatenation is“<manufacturer name> <product name> <model number>”, and the hashfunction may be calculated over the resulting string. Alternatively,newline or tab delimiters may be used. If any of the manufacturer name,product name, or model number is blank or otherwise does not have avalue, that attribute may be represented by an empty string in theconcatenation.

At block 804, normalization application 618 receives model descriptions614 from curated hardware list 612 and compares a calculated hash to thepredetermined hash values in this list. If there is no match, controlreturns to block 802 and new hash value is calculated, this time over adifferent set of parameters. Then, at block 804 once again, this newhash value is compared to those in model descriptions 614.

The process of calculating new hash values at block 802 and comparingthem at block 804 continues until there is a match or there are no morehash values to be calculated in block 802. If a match is found, thennormalization application 618 classifies the type of match as anormalization value. The normalization value indicates the manner inwhich the model entry has been normalized. If there is no match for anycalculated hash value, then the model entry is not in the curatedhardware list 612 and is marked as unnormalized.

As noted, multiple hash values may be calculated for each model entry.Notably, while a model description in curated hardware list 612 may haveonly one set of canonical values for manufacturer name, product name,and model number, it may contain multiple predetermined hash values sothat combinations of these attributes and variations of their values canbe matched.

For example, an entry in curated hardware list 612 may contain separatepredetermined hash values calculated over the following combinations ofattributes: (1) manufacturer name, product name, model number, (2)manufacturer name, model number, and (3) manufacturer name, productname. This allows matching even when not all of the manufacturer name,product name, or model number are present in a model entry of CMDB 500.Support for hash values calculated over variations of attribute valuesmay allow a model entry of CMDB 500 to be matched even when itsattributes contain misspellings and/or abbreviations.

For example, given the hardware model discussed in the context of Table2, suppose that the canonical values for manufacturer name is “TyrellCorp.”, for product name is “RPC”, and for model number is “Z20” incurated hardware list 612. The model description may include numerousmappings between possible hash values and the associated normalizationstatuses. Table 3 represents some of these possible hash values andtheir mapped normalization statuses.

TABLE 3 Line Hash Values Normalization Status 1 Hash1 (“Tyrell Corp. RPCZ20”) Normalized 2 Hash2 (“Tyrell RPC Z20”) Normalized 3 Hash3 (“TyrellInc. RPC Z20”) Normalized 4 Hash4 (“Tyrell Corp. RPC”) PartiallyNormalized 5 Hash5 (“RPC”) Partially Normalized 6 Hash6 (“Tyrell RPC”)Partially Normalized 7 Hash7 (“Tyrell Corp.”) Manufacturer Normalized 8Hash8 (“Tyrell Inc.”) Manufacturer Normalized

For instance, line 1 indicates that, for a model entry being normalized,when the manufacturer name is “Tyrell Corp.”, the product name is “RPC”,and the model number is “Z20”, a hash function calculated over theseattributes matches a predetermined hash value of the canonical values.Thus, the normalization status is “normalized”.

Lines 2 and 3 also result in the normalization status being“normalized”. But in these cases, different ways of representing themanufacturer name, “Tyrell” and “Tyrell Inc.” are used. Thus, the modelentry can have a manufacturer name of “Tyrell” or “Tyrell Inc.” butstill have a normalization status of “normalized”. These entries takeinto account how different discovery tools may represent manufacturernames differently.

Line 4 indicates that, for a model entry being normalized, when themanufacturer name is “Tyrell Corp.” and the product name is “RPC” butthe model number cannot be matched, the normalization status of themodel entry is “partially normalized”. Line 5 indicates that a modelentry in which only the product name matches will also be considered“partially normalized”. Line 6 indicates that a model entry in which themanufacturer name is misspelled and the product name matches will alsobe considered “partially normalized”.

Line 7 indicates that when only the manufacturer name is matched, themodel entry is considered “manufacturer normalized”. Line 8 indicatesthat this is the also case when a particular alternative spelling of themanufacturer name is matched.

Given the large number of possible misspellings or alternative spellingsof manufacturer names, product names, and model numbers, the extent ofpredetermined hash values in a model description from curated hardwarelist 612 can grow quite large (e.g., dozens or more).

In possible embodiments of blocks 802, 804, 806, 808, and 810, hashvalues may be calculated over the attributes of a model entry and thencompared to curated hardware list 612 in the following fashion. First,hash values that would result in a normalization status of “normalized”are calculated. These may include hash values calculated over themanufacturer name, product name, and model number, as well asmisspellings and/or alternative spellings thereof. As indicated at block806, if any of these hash values match a predetermined hash value fromcurated hardware list 612, the model entry is marked as “normalized”.

Then, hash values that would result in a normalization status of“partially normalized” are calculated. These may include hash valuescalculated over the manufacturer name and product name or just theproduct name, as well as misspellings and/or alternative spellingsthereof. As indicated at block 808, if any of these hash values match apredetermined hash value from curated hardware list 612, the model entryis marked as “partially normalized”.

Then, hash values that would result in a normalization status of“manufacturer normalized” are calculated. These may include hash valuescalculated over just the manufacturer name, as well as misspellingsand/or alternative spellings thereof. As indicated at block 810, if anyof these hash values match a predetermined hash value from curatedhardware list 612, the model entry is marked as “manufacturernormalized”.

Manual normalization is not explicitly addressed in FIG. 8. Nonetheless,if a user manually updated any of the manufacturer name, product name,or model number of a model entry, the normalization process of FIG. 8may be carried out automatically. If there is a match between any of thecalculated hash values and a predetermined hash value from curatedhardware list 612, the normalization status is set to “manuallynormalized” regardless of what attributes were used in the hashfunction.

C. Example Graphical User Interfaces

FIGS. 9A-9E depict example graphical user interfaces (GUIs) related tohardware normalization. These GUIs may be generated by computationalinstance 322, for example, and provided to a client device related tomanaged network 300. Each of these GUIs provides information aboutnormalized hardware on managed network, regardless of how it wasdiscovered or manually entered, in a fashion that allows rapidassessment of how the hardware has been normalized as well as anyupcoming dates of importance associated with hardware models.

FIG. 9A depicts GUI 900 of a hardware model from CDMB 500. A header ofGUI 900 displays the manufacturer name 902 (“Manufacturer”) and productname 904 (“Name”). GUI 900 also includes a row of tabs, including tab906 and tab 908. When selected as shown in FIG. 9A, tab 906 displaysgeneral information about the hardware model. This includes the modelnumber 910.

FIG. 9B depicts GUI 900 with tab 908 selected. Accordingly, GUI 900displays information regarding how the hardware model was normalized.This includes normalized values for the manufacturer name 912(“Normalized manufacturer”), product name 914 (“Product”), model number916 (“Model”), normalization status 918, and device type 920. Notably,normalization status is 918 “Normalized”, indicating that a manufacturername 912, product name 914, model number 916 were matched. Thus, theseand other attributes have been populated with canonical values for theassociated hardware model in curated hardware list 612. For example,device type 920 has been populated from curated hardware list 612 aswell, in this case with a value of “Computer servers”.

FIG. 9B also displays a second row of tabs, including tab 922 and tab924. When selected as shown in FIG. 9B, tab 922 displays configurationitems (assets) that are of the displayed hardware model. In FIG. 9B,this list consists of just one configuration item (configuration item924), but in general may include any number of configuration items. Eachlisted item is summarized to display information related thereto,including its asset tag and cost.

FIG. 9C depicts GUI 900 with tab 920 selected. Accordingly, GUI 900displays information regarding hardware model lifecycles. This includesend of sale 926, end of support 928, and end of life 930. Theseattributes have been populated with canonical values for the normalizedhardware model in curated hardware list 612. Each of end of sale 926,end of support 928, and end of life 930 is also associated with a dateon which the associated lifecycle phase begins.

FIGS. 9D and 9E depict GUIs that synthesize lifecycle information forhardware models into intuitive displays that rapidly convey importantdetails of this information. For example, GUI 940 of FIG. 9D includesrepresentations of hardware models in section 942 and representationsfor consumable hardware models in section 944.

Hardware devices discussed up to this point (e.g., laptops, desktops,servers, routers, load balancers) are considered to be non-consumable.Consumable hardware devices include items such as cables, peripherals,phones, tablets, etc., which are generally used and then disposed of.Hardware devices may be deemed as non-consumable or consumable by auser. For purposes of the discussion herein consumable hardware deviceswill be treated identically as non-consumable hardware devices.

In any event, section 942 includes panes that indicate the number ofhardware models reaching end of life this month, this quarter, and thisyear. These numbers are displayed prominently in a large font, and areimportant for purposes of strategic IT planning. For instance, an ITdepartment may determine that it needs to replace hardware models thatreach end of life, or purchase support contracts for these hardwaremodels. Notably, the information shown could be for end of sale, end ofsupport, end of extended support, or any other configured lifecyclephase. Section 942 also includes a gauge that visually indicates thenumber and proportion hardware models that were normalized, as well as apie chart that visually indicates that number and proportion of hardwaremodels in each lifecycle phase.

Section 944 displays similar information for consumable hardware models.Further, section 946 indicates the number of days before computationalinstance 322 is scheduled to download a fresh copy of curated hardwarelist 612 (e.g., from a central instance of remote network managementplatform 320).

GUI 950 of FIG. 9E depicts aggregated hardware and software lifecycleinformation for a service. The service may be defined in CMDB 500 toinclude some number of software packages (each with their own respectivelifecycle information from an associated software model) as well ashardware devices (each with their own respective lifecycle informationfrom the associated hardware model). This information is presented inexpandable/collapsible hierarchy 952.

For example, the service shown in hierarchy 952 includes one softwarecomponent and one hardware component. A lifecycle timeline is shown forthe software component, indicating (by quarter) when the softwarecomponent reaches end of life 954 and end of support 956. A similarlifecycle timeline is shown for the hardware component, indicating (alsoby quarter) when the hardware component reaches end of life 958 and endof support 960.

From this display, an IT department can easily identify the servicesthat are at risk due to software or hardware reaching end of life or endof support. Further, the IT department will know months or quartersahead of time when these dates are approaching, and can take action toreplace the at-risk components or ensure that these components haveappropriate support contracts in place.

VII. Example Operations

FIG. 10 is a flow chart illustrating an example embodiment. The processillustrated by FIG. 10 may be carried out by a computing device, such ascomputing device 100, and/or a cluster of computing devices, such asserver cluster 200. However, the process can be carried out by othertypes of devices or device subsystems, such as computational instance322.

The embodiments of FIG. 10 may be simplified by the removal of any oneor more of the features shown therein. Further, these embodiments may becombined with features, aspects, and/or implementations of any of theprevious figures or otherwise described herein.

Block 1000 may involve obtaining, from persistent storage of acomputational instance, a hardware model of a plurality of hardwaremodels, the hardware models specifying types of computing devices thatare disposed upon a managed network associated with the computationalinstance, wherein the hardware models respectively include attributesrepresenting manufacturer names, product names, and model numbers of thecomputing devices. It is possible that not all of these attributes arepopulated for some of the hardware models.

Block 1002 may involve calculating a hash value by applying a hashfunction to at least some of the attributes of the hardware model.

Block 1004 may involve comparing the hash value to a plurality of hashvalues in a curated hardware list, wherein the curated hardware listincludes normalized hardware models that map the hash values tonormalized manufacturer names, normalized product names, or normalizedmodel numbers. In some cases, combinations of normalized manufacturernames, normalized product names, and normalized model numbers can bematched.

Block 1006 may involve determining that the hash value calculated forthe hardware model matches a particular hash value for a normalizedhardware model in the curated hardware list.

Block 1008 may involve updating, in the persistent storage, the hardwaremodel to include at least one of a normalized manufacturer name, anormalized product name, or a normalized model number associated withthe normalized hardware model.

Some embodiments may involve: determining that the particular hash valueis associated with a normalization status, wherein the normalizationstatus is based on the attributes included in or matched using the hashfunction; and updating, in the persistent storage, the hardware model toinclude the normalization status.

In some embodiments, the normalization status indicates that thehardware model is normalized when the normalized manufacturer name, thenormalized product name, and the normalized model number are matchedusing the hash function. Alternatively, the normalization status mayindicate that the hardware model is manufacturer normalized when onlythe normalized manufacturer name is matched using the hash function. Inother alternatives, the normalization status may indicate that thehardware model is partially normalized when a combination of one or moreof the attributes is matched using the hash function, wherein thecombination is other than: (i) the normalized manufacturer name, thenormalized product name, and the normalized model number, and (ii) onlythe normalized manufacturer name is matched using the hash function. Inparticular, matches involving just the product name or a combination ofthe manufacturer name and the product name may result in a normalizationstatus of partially normalized.

Some embodiments may involve: determining that the normalized hardwaremodel is associated with hardware lifecycle data; and updating, in thepersistent storage, the hardware model to include the hardware lifecycledata. In some embodiments, the hardware lifecycle data includes one ormore of an end of sales date, and end of life date, an end of supportdate, or an end of extended support date.

Some embodiments may involve generating and providing for display, on aclient device associated with the managed network, a GUI including afirst row of tabs. The first row of tabs may contain a first tab that,when actuated, causes display of the normalized manufacturer name, thenormalized product name, and the normalized model number. In someembodiments, the GUI also includes a second row of tabs including asecond tab and a third tab, wherein the second tab, when actuated,causes display of one or more representation of hardware devicesdisposed in the managed network and associated with the hardware model,and wherein the third tab, when actuated, displays hardware lifecycledata associated with the normalized hardware model.

Some embodiments may involve hardware lifecycle data that includes datesrelating to phases of manufacturer support for each of the plurality ofhardware models. These embodiments may also involve generating andproviding for display, on a client device associated with the managednetwork, a GUI including counts of the plurality of hardware models thatare reaching one or more of the dates in a next month, a next quarter,or a next year.

Some embodiments may involve hardware lifecycle data that includes datesrelating to phases of manufacturer support for each of the plurality ofhardware models, wherein software lifecycle data includes dates relatingto phases of manufacturer support for each of a plurality of softwaremodels, wherein the hardware model and a software model from theplurality of software models are both involved in providing a servicedeployed in the managed network. These embodiments may also involvegenerating and providing for display, on a client device associated withthe managed network, a GUI including a timeline displaying the datesrelating to phases of manufacturer support for the hardware model andthe dates relating to phases of manufacturer support for the softwaremodel.

In some embodiments, the curated hardware list was downloaded from acentral instance of the remote network management platform.

In some embodiments, the plurality of hardware models in the persistentstorage were either discovered by probing computing devices disposedupon the managed network or by manual entry.

VIII. Conclusion

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its scope, as will be apparent to thoseskilled in the art. Functionally equivalent methods and apparatuseswithin the scope of the disclosure, in addition to those describedherein, will be apparent to those skilled in the art from the foregoingdescriptions. Such modifications and variations are intended to fallwithin the scope of the appended claims.

The above detailed description describes various features and operationsof the disclosed systems, devices, and methods with reference to theaccompanying figures. The example embodiments described herein and inthe figures are not meant to be limiting. Other embodiments can beutilized, and other changes can be made, without departing from thescope of the subject matter presented herein. It will be readilyunderstood that the aspects of the present disclosure, as generallydescribed herein, and illustrated in the figures, can be arranged,substituted, combined, separated, and designed in a wide variety ofdifferent configurations.

With respect to any or all of the message flow diagrams, scenarios, andflow charts in the figures and as discussed herein, each step, block,and/or communication can represent a processing of information and/or atransmission of information in accordance with example embodiments.Alternative embodiments are included within the scope of these exampleembodiments. In these alternative embodiments, for example, operationsdescribed as steps, blocks, transmissions, communications, requests,responses, and/or messages can be executed out of order from that shownor discussed, including substantially concurrently or in reverse order,depending on the functionality involved. Further, more or fewer blocksand/or operations can be used with any of the message flow diagrams,scenarios, and flow charts discussed herein, and these message flowdiagrams, scenarios, and flow charts can be combined with one another,in part or in whole.

A step or block that represents a processing of information cancorrespond to circuitry that can be configured to perform the specificlogical functions of a herein-described method or technique.Alternatively or additionally, a step or block that represents aprocessing of information can correspond to a module, a segment, or aportion of program code (including related data). The program code caninclude one or more instructions executable by a processor forimplementing specific logical operations or actions in the method ortechnique. The program code and/or related data can be stored on anytype of computer readable medium such as a storage device including RAM,a disk drive, a solid state drive, or another storage medium.

The computer readable medium can also include non-transitory computerreadable media such as computer readable media that store data for shortperiods of time like register memory and processor cache. The computerreadable media can further include non-transitory computer readablemedia that store program code and/or data for longer periods of time.Thus, the computer readable media may include secondary or persistentlong term storage, like ROM, optical or magnetic disks, solid statedrives, or compact-disc read only memory (CD-ROM), for example. Thecomputer readable media can also be any other volatile or non-volatilestorage systems. A computer readable medium can be considered a computerreadable storage medium, for example, or a tangible storage device.

Moreover, a step or block that represents one or more informationtransmissions can correspond to information transmissions betweensoftware and/or hardware modules in the same physical device. However,other information transmissions can be between software modules and/orhardware modules in different physical devices.

The particular arrangements shown in the figures should not be viewed aslimiting. It should be understood that other embodiments can includemore or less of each element shown in a given figure. Further, some ofthe illustrated elements can be combined or omitted. Yet further, anexample embodiment can include elements that are not illustrated in thefigures.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purpose ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims.

What is claimed is:
 1. A computational instance of a remote networkmanagement platform, the computational instance comprising: persistentstorage containing a plurality of hardware models, the hardware modelsspecifying types of computing devices that are disposed upon a managednetwork associated with the computational instance, wherein the hardwaremodels respectively include attributes representing manufacturer names,product names, and model numbers of the computing devices; one or moreprocessors configured to: obtain, from the persistent storage, ahardware model of the plurality of hardware models; calculate a hashvalue by applying a hash function to at least some of the attributes ofthe hardware model; compare the hash value to a plurality of hash valuesin a curated hardware list, wherein the curated hardware list includesnormalized hardware models that map the hash values to normalizedmanufacturer names, normalized product names, or normalized modelnumbers; determine that the hash value calculated for the hardware modelmatches a particular hash value for a normalized hardware model in thecurated hardware list; and update, in the persistent storage, thehardware model to include at least one of a normalized manufacturername, a normalized product name, or a normalized model number associatedwith the normalized hardware model.
 2. The computational instance ofclaim 1, wherein the one or more processors are further configured to:determine that the particular hash value is associated with anormalization status, wherein the normalization status is based on theattributes included in or matched using the hash function; and update,in the persistent storage, the hardware model to include thenormalization status.
 3. The computational instance of claim 2, whereinthe normalization status indicates that the hardware model is normalizedwhen the normalized manufacturer name, the normalized product name, andthe normalized model number are matched using the hash function.
 4. Thecomputational instance of claim 2, wherein the normalization statusindicates that the hardware model is manufacturer normalized when onlythe normalized manufacturer name is matched using the hash function. 5.The computational instance of claim 2, wherein the normalization statusindicates that the hardware model is partially normalized when acombination of one or more of the attributes is matched using the hashfunction, wherein the combination is other than: (i) the normalizedmanufacturer name, the normalized product name, and the normalized modelnumber, and (ii) only the normalized manufacturer name is matched usingthe hash function.
 6. The computational instance of claim 1, wherein theone or more processors are further configured to: determine that thenormalized hardware model is associated with hardware lifecycle data;and update, in the persistent storage, the hardware model to include thehardware lifecycle data.
 7. The computational instance of claim 6,wherein the hardware lifecycle data includes one or more of an end ofsales date, and end of life date, an end of support date, or an end ofextended support date.
 8. The computational instance of claim 1, whereinthe one or more processors are further configured to: generate andprovide for display, on a client device associated with the managednetwork, a graphical user interface (GUI) including a first row of tabs,wherein the first row of tabs contains a first tab that, when actuated,causes display of one or more of the normalized manufacturer name, thenormalized product name, or the normalized model number.
 9. Thecomputational instance of claim 8, wherein the GUI also includes asecond row of tabs including a second tab and a third tab, wherein thesecond tab, when actuated, causes display of one or more representationsof hardware devices disposed in the managed network and associated withthe hardware model, and wherein the third tab, when actuated, displayshardware lifecycle data associated with the normalized hardware model.10. The computational instance of claim 1, wherein hardware lifecycledata includes dates relating to phases of manufacturer support for eachof the plurality of hardware models, and wherein the one or moreprocessors are further configured to: generate and provide for display,on a client device associated with the managed network, a graphical userinterface (GUI) including counts of the plurality of hardware modelsthat are reaching one or more of the dates in a next month, a nextquarter, or a next year.
 11. The computational instance of claim 1,wherein hardware lifecycle data includes dates relating to phases ofmanufacturer support for each of the plurality of hardware models,wherein software lifecycle data includes dates relating to phases ofmanufacturer support for each of a plurality of software models, whereinthe hardware model and a software model from the plurality of softwaremodels are both involved in providing a service deployed in the managednetwork, and wherein the one or more processors are further configuredto: generate and provide for display, on a client device associated withthe managed network, a graphical user interface (GUI) including atimeline displaying the dates relating to phases of manufacturer supportfor the hardware model and the dates relating to phases of manufacturersupport for the software model.
 12. The computational instance of claim1, wherein the curated hardware list was downloaded from a centralinstance of the remote network management platform.
 13. Thecomputational instance of claim 1, wherein the plurality of hardwaremodels in the persistent storage were either discovered by probingcomputing devices disposed upon the managed network or by manual entry.14. A computer-implemented method comprising: obtaining, from persistentstorage of a computational instance, a hardware model of a plurality ofhardware models, the hardware models specifying types of computingdevices that are disposed upon a managed network associated with thecomputational instance, wherein the hardware models respectively includeattributes representing manufacturer names, product names, and modelnumbers of the computing devices; calculating a hash value by applying ahash function to at least some of the attributes of the hardware model;comparing the hash value to a plurality of hash values in a curatedhardware list, wherein the curated hardware list includes normalizedhardware models that map the hash values to normalized manufacturernames, normalized product names, or normalized model numbers;determining that the hash value calculated for the hardware modelmatches a particular hash value for a normalized hardware model in thecurated hardware list; and updating, in the persistent storage, thehardware model to include at least one of a normalized manufacturername, a normalized product name, or a normalized model number associatedwith the normalized hardware model.
 15. The computer-implemented methodof claim 14, further comprising: determining that the particular hashvalue is associated with a normalization status, wherein thenormalization status is based on the attributes included in or matchedusing the hash function; and updating, in the persistent storage, thehardware model to include the normalization status.
 16. Thecomputer-implemented method of claim 14, further comprising: determiningthat the normalized hardware model is associated with hardware lifecycledata; and updating, in the persistent storage, the hardware model toinclude the hardware lifecycle data.
 17. The computer-implemented methodof claim 16, wherein the hardware lifecycle data includes one or more ofan end of sales date, and end of life date, an end of support date, oran end of extended support date.
 18. The computer-implemented method ofclaim 14, further comprising: generating and providing for display, on aclient device associated with the managed network, a graphical userinterface (GUI) including: a first row of tabs, wherein the first row oftabs contains a first tab that, when actuated, causes display of one ormore of the normalized manufacturer name, the normalized product name,or the normalized model number.
 19. The computer-implemented method ofclaim 14, wherein hardware lifecycle data includes dates relating tophases of manufacturer support for each of the plurality of hardwaremodels, wherein the computer-implemented method further comprises:generating and providing for display, on a client device associated withthe managed network, a graphical user interface (GUI) including countsof the plurality of hardware models that are reaching one or more of thedates in a next month, a next quarter, or a next year.
 20. An article ofmanufacture including a non-transitory computer-readable medium, havingstored thereon program instructions that, upon execution by a computingsystem, cause the computing system to perform operations comprising:obtaining, from persistent storage of a computational instance, ahardware model of a plurality of hardware models, the hardware modelsspecifying types of computing devices that are disposed upon a managednetwork associated with the computational instance, wherein the hardwaremodels respectively include attributes representing manufacturer names,product names, and model numbers of the computing devices; calculating ahash value by applying a hash function to at least some of theattributes of the hardware model; comparing the hash value to aplurality of hash values in a curated hardware list, wherein the curatedhardware list includes normalized hardware models that map the hashvalues to normalized manufacturer names, normalized product names, ornormalized model numbers; determining that the hash value calculated forthe hardware model matches a particular hash value for a normalizedhardware model in the curated hardware list; and updating, in thepersistent storage, the hardware model to include at least one of anormalized manufacturer name, a normalized product name, or a normalizedmodel number associated with the normalized hardware model.